Publications by authors named "Silvia Ingala"

Purpose: To evaluate the performance of an AI tool and relevant radiology professionals in detecting brain infarcts, intracranial hemorrhages, and tumors using abbreviated brain MRI scan protocols as prerequisite for an AI-driven workflow that dynamically selects additional imaging sequences based on real-time imaging findings.

Materials And Methods: A retrospective, consecutively enriched cohort of routine adult brain MRI scans from four Danish hospitals was constructed. Three consultant neuroradiologists, three radiology residents, three MR technologists, and an AI tool detected brain infarcts, hemorrhages, and tumors using an abbreviated 3-sequence protocol (DWI, SWI/T2*-GRE, T2-FLAIR) or 4-sequence protocol (DWI, SWI/T2*-GRE, T2-FLAIR, T1W) in a non-overlapping three-way split cross-over design.

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Reliable reading and annotation of chest X-ray (CXR) images are essential for both clinical decision-making and AI model development. While most of the literature emphasizes pulmonary findings, this study evaluates the consistency and reliability of annotations for extrapulmonary findings, using a labelling scheme. Six clinicians with varying experience levels (novice, intermediate, and experienced) annotated 100 CXR images using a diagnostic labelling scheme, in two rounds, separated by a three-week washout period.

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: Approximately 50% of all oncological patients undergo radiation therapy, where personalized planning of treatment relies on gross tumor volume (GTV) delineation. Manual delineation of GTV is time-consuming, operator-dependent, and prone to variability. An increasing number of studies apply artificial intelligence (AI) techniques to automate such delineation processes.

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Introduction: Identifying the link between early Alzheimer's disease (AD) pathological changes and neurodegeneration in asymptomatic individuals may lead to the discovery of preventive strategies. We assessed longitudinal brain atrophy and cognitive decline as a function of cerebrospinal fluid (CSF) AD biomarkers in two independent cohorts of cognitively unimpaired (CU) individuals.

Methods: We used longitudinal voxel-based morphometry (VBM) in combination with hippocampal subfield segmentation.

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Importance: Baseline cerebral microbleeds (CMBs) and APOE ε4 allele copy number are important risk factors for amyloid-related imaging abnormalities in patients with Alzheimer disease (AD) receiving therapies to lower amyloid-β plaque levels.

Objective: To provide prevalence estimates of any, no more than 4, or fewer than 2 CMBs in association with amyloid status, APOE ε4 copy number, and age.

Design, Setting, And Participants: This cross-sectional study used data included in the Amyloid Biomarker Study data pooling initiative (January 1, 2012, to the present [data collection is ongoing]).

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Background And Objectives: Vascular risk factors (VRFs) and cerebral small vessel disease (cSVD) are common in patients with Alzheimer disease (AD). It remains unclear whether this coexistence reflects shared risk factors or a mechanistic relationship and whether vascular and amyloid pathologies have independent or synergistic influence on subsequent AD pathophysiology in preclinical stages. We investigated links between VRFs, cSVD, and amyloid levels (Aβ) and their combined effect on downstream AD biomarkers, that is, CSF hyperphosphorylated tau (P-tau), atrophy, and cognition.

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Article Synopsis
  • The study explores the genetic risk factors for Alzheimer's disease (AD) and their connection to various brain changes, aiming to enhance precision medicine strategies.
  • Researchers calculated specific genetic risk scores in healthy individuals to see how these scores correlate with AD-related biomarkers found in cerebrospinal fluid and imaging techniques.
  • Findings show that different genetic pathways link to distinct brain conditions, such as inflammation affecting vascular health and other pathways influencing white matter and brain connectivity, highlighting the complexity of AD and its potential for personalized treatment approaches.
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Objective: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults.

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Article Synopsis
  • Recent research is advancing cost-effective methods for detecting amyloid pathology in Alzheimer's disease using non-invasive biomarkers, particularly through imaging and demographic factors.
  • A comprehensive study utilized a diverse dataset from various cohorts, focusing on the effectiveness of multimodal biomarkers and machine learning to identify amyloid plaques.
  • Results showed that incorporating demographic data significantly improved detection accuracy, especially in early-stage Alzheimer's, suggesting the potential for refining these approaches with additional genetic and plasma markers.
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DWI/FLAIR mismatch assessment for ischemic stroke patients shows promising results in determining if patients are eligible for recombinant tissue-type plasminogen activator (r-tPA) treatment. However, the mismatch criteria suffer from two major issues: binary classification of a non-binary problem and the subjectiveness of the assessor. In this article, we present a simple automatic method for segmenting stroke-related parenchymal hyperintensities on FLAIR, allowing for an automatic and continuous DWI/FLAIR mismatch assessment.

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Article Synopsis
  • Imaging markers of cerebral small vessel disease can provide insights into brain health, but their manual assessment is slow and has high variability among different evaluators.
  • The VALDO challenge, held alongside the MICCAI 2021 conference, aimed to develop automated methods for detecting specific brain imaging markers, including enlarged perivascular spaces, cerebral microbleeds, and lacunes, using imperfect data.
  • The results highlighted significant performance differences among 12 participating teams, showing promise for detecting enlarged perivascular spaces and microbleeds, but indicating that solutions for lacunes remain less effective for individual use despite potential benefits for population studies.
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Aging-related cognitive decline can be accelerated by a combination of genetic factors, cardiovascular and cerebrovascular dysfunction, and amyloid-β burden. Whereas cerebral blood flow (CBF) has been studied as a potential early biomarker of cognitive decline, its normal variability in healthy elderly is less known. In this study, we investigated the contribution of genetic, vascular, and amyloid-β components of CBF in a cognitively unimpaired (CU) population of monozygotic older twins.

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Amyloid-β accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer's disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time.

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Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS.

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Gray matter networks are altered with amyloid accumulation in the earliest stage of AD, and are associated with decline throughout the AD spectrum. It remains unclear to what extent gray matter network abnormalities are associated with hyperphosphorylated-tau (p-tau). We studied the relationship of cerebrospinal fluid (CSF) p-tau181 with gray matter networks in non-demented participants from the European Prevention of Alzheimer's Dementia (EPAD) cohort, and studied dependencies on amyloid and cognitive status.

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Article Synopsis
  • This article updates the 2015 consensus paper on arterial spin labeling (ASL) MRI, focusing on its clinical applications and guiding use in specific diseases.
  • It addresses the increased demand and applications of ASL in conditions like stroke, brain tumors, and neurodegenerative diseases, offering insights on optimizing sequences for accurate interpretation.
  • The guidance aims to assist clinical practitioners in implementing ASL in individual patient assessments rather than just in research studies, enhancing diagnostic capabilities.
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  • Chest trauma often necessitates both invasive and non-invasive ventilation methods, with limited studies exploring factors predictive of ventilatory support needs.
  • Analysis of data from 1080 chest trauma patients revealed that rib fractures, certain other fractures, hemothorax, pulmonary contusion, and high Injury Severity Scores (ISS) were key predictors for requiring tracheal intubation and non-invasive mechanical ventilation.
  • Factors such as the trauma center's expertise, patient age, oxygen saturation, ISS, and Revised Trauma Score significantly influenced patient outcomes, indicating that certain injuries may allow for non-invasive support rather than intubation.
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Several studies have shown decreased cerebral blood flow (CBF) in Alzheimer's disease (AD). However, the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, PET, and CSF biomarkers, we investigated the associations between gray matter (GM)-CBF and the key mechanisms in AD including amyloid-β (Aβ) and tau pathology, synaptic and axonal degeneration.

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Background: Patients with vascular cognitive impairment (VCI) are very heterogeneous in both symptoms and type of cerebrovascular pathology. This might be an important reason why there is no symptomatic treatment available for VCI patients. In this study, we investigated in patients with VCI, whether there was an association between a positive response to methylphenidate and galantamine and the type of cerebrovascular disease, structural damage to specific neurotransmitter systems, cerebral perfusion, and presence of co-morbid Alzheimer (AD) pathology.

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The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset.

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White matter hyperintensities (WMHs) have a heterogeneous aetiology, associated with both vascular risk factors and amyloidosis due to Alzheimer's disease. While spatial distribution of both amyloid and WM lesions carry important information for the underlying pathogenic mechanisms, the regional relationship between these two pathologies and their joint contribution to early cognitive deterioration remains largely unexplored. We included 662 non-demented participants from three Amyloid Imaging to Prevent Alzheimer's disease (AMYPAD)-affiliated cohorts: EPAD-LCS (N = 176), ALFA+ (N = 310), and EMIF-AD PreclinAD Twin60++ (N = 176).

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Objectives: Neurodegeneration in suspected Alzheimer's disease can be determined using visual rating or quantitative volumetric assessments. We examined the feasibility of volumetric measurements of gray matter (GMV) and hippocampal volume (HCV) and compared their diagnostic performance with visual rating scales in academic and non-academic memory clinics.

Materials And Methods: We included 231 patients attending local memory clinics (LMC) in the Netherlands and 501 of the academic Amsterdam Dementia Cohort (ADC).

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Accurate and realistic simulation of high-dimensional medical images has become an important research area relevant to many AI-enabled healthcare applications. However, current state-of-the-art approaches lack the ability to produce satisfactory high-resolution and accurate subject-specific images. In this work, we present a deep learning framework, namely 4D-Degenerative Adversarial NeuroImage Net (4D-DANI-Net), to generate high-resolution, longitudinal MRI scans that mimic subject-specific neurodegeneration in ageing and dementia.

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Cortical accumulation of amyloid beta is one of the first events of Alzheimer's disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer's disease.

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Introduction: Amyloid beta (Aβ) accumulation is the first pathological hallmark of Alzheimer's disease (AD), and it is associated with altered white matter (WM) microstructure. We aimed to investigate this relationship at a regional level in a cognitively unimpaired cohort.

Methods: We included 179 individuals from the European Medical Information Framework for AD (EMIF-AD) preclinAD study, who underwent diffusion magnetic resonance (MR) to determine tract-level fractional anisotropy (FA); mean, radial, and axial diffusivity (MD/RD/AxD); and dynamic [F]flutemetamol) positron emission tomography (PET) imaging to assess amyloid burden.

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